composition and dynamics of the great phanerozoic evolutionary floras

Composition and dynamics of the great PhanerozoicEvolutionary Floras

CHRISTOPHER J. CLEAL AND BORJA CASCALES-MI~NANA

Cleal, C.J. & Cascales-Mi~nana, B. 2014: Composition and dynamics of the greatPhanerozoic Evolutionary Floras. Lethaia, DOI: 10.1111/let.12070.

Factor analysis of a data set representing the global distribution of vascular plant fami-lies through time shows the broad pattern of vegetation history can be explained interms of five Evolutionary Floras. The Rhyniophytic (=Eotrachyophytic) Flora repre-sents the very earliest (Silurian and earliest Devonian) vascular plants, notably theRhyniophytopsida. The Eophytic Flora represents the early (Early–Middle Devonian)mainly homosporous land plants, notably the Zosterophyllopsida, Trimerophytopsidaand early Lycopsida. The Palaeophytic Flora represents the Late Devonian and Carbo-niferous vegetation, which saw the introduction of heterospory among the spore pro-ducing plants and of early gymnosperms. The Mesophytic Flora first appeared in theLate Carboniferous and Permian macrofossil record, although there is palynologicalevidence of these plants having grown earlier in extra-basinal habitats and was domi-nated by gymnosperms with more modern affinities. The Cenophytic Flora that firstappeared during Cretaceous times was overwhelmingly dominated by angiosperms.The end-Devonian, end-Triassic and end-Cretaceous mass-extinction events recog-nized in the marine fossil record had little impact on the diversity dynamics of theseEvolutionary Floras. Rather, the changes between floras mainly reflect key evolution-ary innovations such as heterospory, ovules and angiospermy. □ Diversity, Evolution-ary Floras, extinction events, families, palaeobotany.

Christopher J. Cleal [[email protected]], and Borja Cascales-Mi~nana[[email protected]; [email protected]], Department of Natural Sciences,National Museum Wales, Cathays Park Cardiff CF10 3NP, UK; AMAP (Botanique etBioinformatique de l0Architecture des Plantes), UMR5120 CNRS-CIRAD,Montpellier Cedex 5F-34398, France; manuscript received on 22/11/2013; manuscriptaccepted on 04/02/2014.

There have been attempts to find large-scale patternsin the fossil record since early in the development ofscientific palaeontology (Cuvier 1825; Brongniart1828a; Phillips 1860). In recent years, this has mostlyfocused on determining patterns of taxonomicdiversity at various ranks, with the aim of identifyingand interpreting significant times of diversificationand extinction (see Sepkoski 2012 for a review).However, it has also become evident that it is impor-tant to take into account the ecological changes thataccompanied these changes in taxonomic diversity(McGhee et al. 2004, 2012, 2013; Droser et al.2013). As an intermediate aspect of this type ofanalysis, palaeozoologists have been grouping taxainto faunal communities that combine phylogenetic/evolutionary and ecological signals, most notablyEcological Evolutionary Units of Boucot (1983) andSheehan (1996) (which DiMichele 1994 equatedwith biomes) and the larger scale Diversity Associa-tions of Flessa & Imbrie (1975) and EvolutionaryFaunas of Sepkoski (1979, 1981, 1984, 1990).

This work has mainly focused on the fossil recordof marine invertebrates such as compiled by Harlandet al. (1967), Sepkoski (1982, 1992) and Benton

(1993). However, there is also historical precedencefor identifying large-scale patterns in the fossil his-tory of terrestrial vegetation, such as the recognitionof Palaeophytic, Mesophytic and Cenophytic florasby Gothan (1912) and Potoni�e (1921). This was fur-ther developed by Niklas et al. (1983), who pro-posed a set of what they called Evolutionary Phasesbased on a species compilation derived from theplant macrofossil record and illustrated a model(Niklas et al. 1983, fig. 1) that is still often repro-duced in the scientific literature (e.g. Haworth et al.2011, fig. 1). As we will show later, however, thereare considerable uncertainties surrounding themethodology used by Niklas et al. (1983), makingtheir model difficult to compare with Sepkoski’s(1982) Evolutionary Faunas. In the present paper,therefore, we have adopted exactly the same mathe-matical approach as used by Sepkoski (1981) andapplied it to the most recent compilation of familiesand classes of tracheophytes (vascular plants) asrevealed in the fossil record. We provide herein fulldetails of the analysis, and from this, we present thefirst rigorously developed model of EvolutionaryFloras that are directly comparable with Sepkoski’s

DOI 10.1111/let.12070 © 2014 Lethaia Foundation. Published by John Wiley & Sons Ltd

(1982) Evolutionary Faunas. This will, for the firsttime, allow an objective comparison between thelarge-scale taxonomic groupings in plants and mar-ine invertebrates, which in turn will go some way toaddress the issue raised by Traverse (1988) and Val-entine et al. (1991): how do the large-scale evolu-tionary dynamics in these two groups of organismscompare?

Evolutionary Faunas

Sepkoski (1979, 1984) initially formulated his con-cept of Evolutionary Faunas as a by-product ofdeveloping a kinetic model to explain taxonomicdiversity changes among Phanerozoic marine inver-tebrates. He further developed the concept by analy-sing the fossil record using factor analysis (Sepkoski1981), which revealed three of what he called Evolu-tionary Faunas: the Cambrian, Palaeozoic and Meso-zoic–Cenozoic (or Modern) faunas. The classes ineach fauna were interpreted as sharing several char-acteristics and as tending to diversify together (Sep-koski 1990). They were not randomly assembledgroups of taxa and could therefore be regarded ashaving a macroevolutionary coherence, thereby pro-viding a useful means of explaining the overarchingtrajectory of evolution among these invertebrates(Sepkoski 1979, 1984).

The model initially became widely accepted (Bam-bach 1985; Van Valen 1985; for a more completereview, see Alroy 2004); as Sepkoski (1981) himselfpointed out, the observed pattern of changes seemedto agree with the instincts of most palaeontologists.A similar model was also developed by Benton(1985, 1987) for non-marine tetrapod vertebrates –although using a different methodological approach.However, Sepkoski (1979, 1984) also tried todevelop macroevolutionary ideas from these obser-vations, which were more contentious, notably thatfaunal diversity followed an essentially logistic pat-tern, eventually achieving an equilibrium state dueto limitations in the carrying capacity of the envi-ronment, and that faunal replacement was a conse-quence of the intrinsic background speciation andextinction rates of each fauna (Sepkoski 1990). Theseideas about process have attracted criticism (Hoff-man 1985; Hoffman & Fenster 1986; Benton 2001).Stanley (2007), for instance, argued that overall tax-onomic diversification in marine faunas hasremained essentially exponential through geologicaltime and that the observed flattening of diversitycurves was a consequence of the dampening effect ofmajor extinction events and climate change. Alroy

(2004) also pointed out that this type of factoranalysis model tends to emphasize the family-richclades and that the association of the smaller cladesto the resulting factors/faunas is less reliable. Never-theless, Sepkoski’s Evolutionary Faunas model is stillwidely invoked as a useful way of looking at large-scale changes in the marine faunas (Miller 2012;Leighton et al. 2013).

Evolutionary Floras

Since the pioneering work of von Sternberg (1820–1825) and Brongniart (1828a, 1828b–1838), it hasbeen evident that there were broad changes in plantlife between the Palaeozoic, Mesozoic and Cenozoiceras and eventually the concepts of Palaeophytic,Mesophytic and Cenophytic floras became estab-lished (Gothan 1912; Potoni�e 1921). In this model,Palaeophytic vegetation was dominated by pterido-phytes (Lycopsida, Equisetopsida and early ferns)and early gymnosperms; Mesophytic vegetation bymore modern ferns and gymnosperms; and Ceno-phytic vegetation by angiosperms. However,although Gothan (1912) was defining these florasbased on the stratigraphical distribution of plant fos-sils (i.e. in what we would today call a biostrati-graphical way), he was clearly envisaging them as ineffect time units (i.e. they were chronostratigraphicalin nature). This conflation of biostratigraphy andchronostratigraphy was widespread throughout pal-aeontology in the first half of the 20th century andcaused much confusion; the problem was not reallyresolved until the introduction of the first Interna-tional Stratigraphic Code (Hedberg 1976), whichestablished a clear demarcation between biostratigra-phy and chronostratigraphy. Gothan’s (1912)scheme in fact exemplified the problems that couldarise from this conflation. It soon became evident,for instance, that not only did the Mesophytic Floranot coincide with the Mesozoic Era (Gothan & Wey-land 1954), but its lower and upper boundaries werediachronous: Mesophytic vegetation appears to haveevolved in extra-basinal habitats in at least Late Car-boniferous times and progressively replaced Palaeo-phytic vegetation during Permian times, and itbegan to be progressively replaced by Cenophyticvegetation during Cretaceous times (Frederiksen1972; Traverse 1988). Partly for this reason, somepalaeobotanists have argued that these floras havelittle conceptual value and should be abandoned(Kerp 1996, 2000; DiMichele et al. 2008). Others,however, have recognized that provided their chro-nostratigraphical baggage is abandoned and they are

2 C. J. Cleal & B. Cascales-mi~nana LETHAIA 10.1111/let.12070

viewed purely as biostratigraphical–palaeobiogeo-graphical concepts, such floras do have relevance fordescribing the overarching trajectory of vegetationhistory, and a number of more complex models havebeen developed (Krishtofovich 1957; Banks 1970;Vakhrameev et al. 1978; Vakhrameev 1991; Gray1993).

The analogy between such floras and Sepkoski’s(1981) Evolutionary Faunas was recognized by Nik-las et al. (1983), who identified four of what theyreferred to as ‘Evolutionary Phases’ (later authorsactually referred to them as Evolutionary Floras –for example Jablonski & Sepkoski 1996): theseapproximate to the three Gothan (1912) floras, plusa Silurian–Devonian early land plant flora. Niklaset al. (1983, fig. 1) showed their interpretation of thechanging species diversities of plants through timeof the four groups and the caption implied that thisoutput had been generated through factor analysis(a redrawn version of this figure is shown here,Fig. 1); in a later paper, they also mentioned plantgroups that belong to factors (Niklas et al. 1985,fig. 1). However, no details of a factor analysis haveever been published, and the discussion in Niklaset al. (1983) and the labelling of their Figure 1 sug-gested that these groups were not factors in anymathematical sense, nor did they relate directly tothe Gothan (1912) floras – they appear to have beenmerely groups of taxa chosen a priori: (1) early vas-cular plants; (2) other pteridophytes; (3) gymno-sperms; and (4) angiosperms (a similar but moredetailed approach was later used by Niklas et al.1985). The confusion was amplified by Sepkoski’s(1990, p. 40) comments on Niklas et al. (1983),where he stated that, for instance, the second group

comprised ‘a pteridophyte-dominated flora, includ-ing ferns, lycopods, sphenopsids and progymno-sperms’, which does have more of the flavour of afactor analysis result. Although the iconic diagramshown in Niklas et al. (1983, fig. 1) has regularlybeen re-illustrated (e.g. Haworth et al. 2011, fig. 1),it is difficult to know what it really means as we donot know how it was generated.

There is, moreover, a problem with using fossilspecies for this sort of analysis. Palaeobotanical spe-cies are conceptually different from most palaeozoo-logical species as they do not represent wholeorganisms: there are separate sets of palaeobotanicalfossil species for the different parts that made up theoriginal organism (leaves, ovules, stems, etc.) andfor the different modes of preservation that they arefound in (Cleal & Thomas 2010). As different plantgroups are represented by different numbers of fossilspecies, they provide a highly distorted signal of theoriginal plant diversity and of vegetation history(Cleal et al. 2012; Cascales-Mi~nana et al. 2013). Forinstance, among Late Carboniferous tropical wetlandvegetation, the arborescent Lycopsida are repre-sented in the adpression record by six sets of fossilspecies, whereas the Medullosales pteridosperms arerepresented by only three sets of fossil species; but ifanatomically preserved fossils are considered, theseLycopsida are usually represented by three or foursets of fossil species (depending on whether or not aparticular group had bisporangiate cones), whereasthere are five sets of species for the Medullosales. Asthe Niklas et al. (1983) data set has never been pub-lished (and reportedly it was subsequently modified– Niklas & Tiffney 1994), it is unclear how theyattempted to overcome this problem of distortion in

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Fig. 1. Changing species diversities through time of the major groups of vascular plants as recorded by Niklas et al. (1983, 1985). Theupper thick black line represents total species diversity including non-vascular plants and incertae sedis. Redrawn from Niklas et al.(1983, fig. 1) with time-scale adjusted to correspond with the latest IUGS chronostratigraphical scheme (Cohen et al. 2013).

LETHAIA 10.1111/let.12070 Phanerozoic Evolutionary Floras 3

species diversity patterns in the palaeobotanicalrecord.

In contrast, most palaeobotanical supragenerictaxa tend to be clustered around whole, recon-structed fossil plants, with their taxonomic circum-scriptions and distributional ranges (geographicaland temporal) being extrapolated using the taxo-nomically more reliable (at that rank) of the plantfossil data, mainly from reproductive organs andanatomy (for instance, see the approach used byAnderson et al. 2007). We therefore believe that cur-rently these provide a more accurate picture of thebroad trends of vegetation history than diversitydata based on fossil species (unless those data havebeen normalized, such as in Cleal et al. 2012). Thereare now available data sets showing the stratigraphi-cal distribution of suprageneric plant taxa, which arepublished and were based on a critical taxonomicevaluation of the data (Benton 1993; Collinson 1996;Anderson et al. 2007). Using the same methodologi-cal approach as adopted by Sepkoski (1981) with themarine invertebrate faunas, we have therefore usedthese palaeobotanical data to see whether anythinganalogous to the Evolutionary Faunas can be recog-nized and whether they can be compared to theGothan (1912) model (in its floristic rather thanchronostratigraphical sense) and which may helpwith the interpretation of vegetation history.

Data and methods

Data and taxonomic classification

Following the approach used by Sepkoski (1981),we analysed the variation in family diversity withinthe classes of vascular plants through the Cascales-Mi~nana & Cleal (2014) data set. There have beencriticisms of using higher taxa for this sort ofanalysis because of subjectivity of their definition(Patterson & Smith 1987). However, subjectivity isa problem at all ranks in palaeontological taxon-omy, including species, and we would argue thatfamilies and classes are no worse than other ranks.The taxonomic classifications of vascular plantsgiven in Benton (1993), Collinson (1996) andAnderson et al. (2007), on which our analysis wasbased, have remained relatively stable for sometime and are compatible with the most recentlyproposed classifications that integrate botanical andpalaeobotanical evidence (Smith et al. 2006; Chase& Reveal 2009; Christenhusz et al. 2011). The revi-sions that have taken place (e.g. Krassilov 2009)have mostly been at the rank of order and thus donot affect our analysis.

Analytical methodology

Using the same approach as Sepkoski (1981), weused Q-mode factor analysis to investigate thematrix of the number of families in each class of vas-cular plants for each stratigraphical age. There hasbeen much debate about the use of factor analysis ingeological and palaeontological studies, and espe-cially how it relates to the conceptually simpler prin-cipal components analysis (PCA; Davies 1973;Temple 1978; Kufs 1979; Reyment & Jvreskog 1996;Hammer & Harper 2006). Both use eigenvectoranalysis to help reduce dimensionality in a multi-variate data set. PCA uses the same number of newvariables (referred to as eigenvectors or compo-nents) as there were in the original data set, but, ifthe analysis is successful, a significantly high portionof the variance (the eigenvalues) is focused on just afew of those components (the principal compo-nents). Consequently, the data can be interpreted onthose principal components (usually two or three)that represent the highest eigenvalues. We attemptedto use PCA on a normalized form of our data (i.e.using its correlation matrix), but the results weredisappointing. Seven components were required toexplain 90% of the variance, and those componentshad little taxonomic or stratigraphical meaning. Thisapproach was therefore abandoned.

Factor analysis uses a more aggressive approachto extracting patterns from a multivariate data set.As with Flessa & Imbrie (1975) and Sepkoski(1981), the Imbrie & Kipp (1971) CABFAC ver-sion of Q-mode factor analysis was used (asimplemented in the PAST statistical package –Hammer et al. 2001). Orthogonal eigenvectors(here known as factors) are first extracted fromthe data and a decision made as to how many areto be used in the analysis. There is no definitivemethod of deciding on the number of factors touse. Sepkoski (1981), for instance, used the ‘screetest’, where the eigenvalues represented by eachsuccessive factor are plotted logarithmically; anabrupt break in the slope of the resulting line isused to select the number of factors (Cattell 1966suggested that the factor after the change in slopeshould be the highest one used). Alternativeapproaches are only to use factors with eigenvaluesof 1.0 or more (the so-called Kaiser rule) or tokeep on adding factors until 80% or 90% of thetotal variance is explained. Flessa & Imbrie (1975)also argued that the factors should be rejected ifthey did not provide meaningful resolution of thedata. As there is no consensus on the best meth-odology, a combination of these approaches wasused in our study.


These resulting factors are then rotated to what istermed ‘simple structure’ with the aim of makingthe results easier to interpret. This is one of the morecontentious features of factor analysis, with variousstrategies having been proposed, but one of the mostwidely used and (arguably) objective is Kaiser’s(1958) Varimax rotation. This rotates the factors sothat each tends to have high scores of some variablesand low scores of others (see Davies 1973 for anexplanation of this procedure). This should result inthe variables (in this case plant classes) being moreclearly segregated onto different factors than beforethe rotation, making for a more clear-cut resolutionof the data into (in this case) floras. Each factor willrepresent a proportion of the family diversity of eachclass (represented by factor scores). The factorsmainly reflect the distribution of the family-richclasses, and the attribution of the less diverse classesto the factors can be less robust, resulting in somelow-level noise in the model (Alroy 2004). Neverthe-less, the approach has proved an effective means ofdetermining patterns of association among the mainclasses of plants and thereby revealing the broad pat-tern of Phanerozoic vegetation history.

Results

Figure 2 shows the changing family diversitiesamong the 20 classes of vascular plants recognized inthis study. There is considerable variation betweenclasses.

1 The shorter lived classes (Rhyniopsida, Horneo-phytopsida, Trimeophytopsida, Noeggerathiopsida,

Axelrodopsida) tended to remain at relatively lowdiversity throughout their ranges.

2 Several classes are relatively long-lived butremained of relatively constant (and usuallylow) family diversity: Marratiopsida, Progymno-spermopsida, Lyginopteridopsida, Bennettitops-ida, Gnetopsida.

3 The diversities of the Lycopsida, Equisetopsidaand Cycadopsida increased during Palaeozoictimes following an essentially logarithmic curvebut then declined towards the end of Palaeozoictimes. They then continued through Mesozoic andCenozoic times to today, at low family diversities.

4 A similar diversity pattern is shown by the Gink-goospida but with a later peak in family diversityin Early Mesozoic times.

5 Two of the most diverse classes in modern vegeta-tion (Pteropsida and Pinopsida) show a bimodaldistribution, with a marked constriction in familydiversity through the Permian/Triassic boundaryinterval.

6 The angiosperms diversified rapidly during LateMesozoic and Cenozoic times following an essen-tially logarithmic curve.

The factor analysis of the data set produced a screeplot with a relatively straight line, indicating nomajor fall-off in the amount of informationexplained by each successive eigenvector (Fig. 3).Such a result could result from a matrix of randomdata, but we do not believe that this is the case here asthe resulting factors with highest eigenvalues appearto be taxonomically and stratigraphically meaningful.The Kaiser rule (using eigenvectors with eigen-values > 1) suggested that the first six eigenvectors

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Fig. 2. Spindle diagram showing temporal changes in family diversities within each of the 20 classes currently recognized within the vas-cular plants. For the purposes of this diagram, the temporal units are taken as stratigraphical ages of constant duration.


should provide a robust explanation of the data set,and this is corroborated by the fact that they repre-sent well over 95% of the total variance (Table 1).

However, factor 6 had both positive and negativescores from a range of different classes and showedno obvious temporal trend. Following the advice ofFlessa & Imbrie (1975), therefore, factor 6 wasrejected and a five-factor model was used. The load-ings on the five rotated factors of successive strati-graphical intervals are shown in Figure 3, and theplant classes that score most heavily on each factorare shown in Table 2.

The 95% of the variance explained in the five-factor model summarized in this paper is a littlehigher than the c. 91% that was accounted for inSepkoski’s (1981) three-factor model for marineinvertebrates. To paraphrase Sepkoski (1981, p.48), the results should be of no real surprise to anypalaeobotanist as they appear to corroborate theexperience of anyone who has walked out a varietyof stratigraphical sections or picked through anumber of museum drawers. They moreover essen-tially corroborate the temporal non-numerical flo-ristic models of Gothan (1912), Gothan & Weyland(1954) and Gray (1993).

The five factors (Fig. 4) in stratigraphical order(rather than in order of increasing eigenvalues) maybe summarized as follows.

Factor 5 (Silurian – earliest Devonian). This is domi-nated by Rhyniopsida and some Lycopsida (Table 2)and is essentially equivalent to the RhyniophyticPhase of Edwards & Selden (1992) and the Eotrachy-ophytic Floras of Gray (1993) (see also Kenrick &Crane 1997a; Bateman et al. 1998; Edwards 1998);we have here adopted the earlier Edwards & Seldenterm and refer to factor 5 as the RhyniophyticFlora. The rather irregular stratigraphical distribu-tion of the loadings of this factor (Fig. 4) is dueto the apparently anomalous scoring of Cycadops-ida, Ottokariopsida, angiosperms, Marratiopsida,

Table 2. Scores of the main plant classes on the five rotated factors (only those classes with scores >0.1 are given). The classes are givenin four groups: scores > 2.0 (factors 1, 3 and 5) or <�2.0 (factors 2 and 4); scores 1–2 (factors 1, 3 and 5) or �1 to �2 (factors 2 and 4);scores 0.5–1.0 (factors 1, 3 and 5) or -0.5 to �1.0 factors 2 and 4); and 0.1–0.5 (factors 1, 3 and 5) or �0.1 to �0.5 (factors 2 and 4).

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5

Pinopsida (4.07) Angiosperms (�4.40) Lycopsida (3.27) Zosterophyllopsida (�4.08) Rhyniopsida (3.78)

Ginkgoopsida (1.44) Pteropsida (1.94) Lycopsida (�1.03)

Pteropsida (1.05) Equisetopsida (1.30) Lycopsida (1.31)Cycadopsida (1.04)

Bennettitopsida (0.62) Pteropsida (�0.74) Lyginopteridopsida (0.84) Rhyniopsida (�0.96)Progymnospermopsida (0.61)

Lycopsida (0.43) Pinopsida (�0.29) Marratiopsida (0.39) Cycadopsida (0.44)Cycadopsida (0.38) Trimerophytopsida (�0.44) Ottokariopsida (0.32)Marratiopsida (0.27) Angiosperms (0.28)Equisetopsida (0.22) Gnetopsida (�0.10) Ottokariopsida (0.21) Horneophytopsida (�0.11) Marratiopsida (0.27)Gnetopsida (0.15) Ginkgoopsida (0.21)Ottokariopsida (0.13) Pinopsida (0.10)

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Fig. 3. Scree plot of the eigenvalues for the successive eigenvec-tors generated by factor analysis.

Table 1. Eigenvalues for the first ten eigenvectors generated bythe CABFAC factor analysis of family diversity data within vascu-lar plant families through successive stratigraphical ages from theHomerian Age (Silurian Period) to the Pleistocene Epoch.

Eigenvector Eigenvalue % Variance

1 38.83 51.782 18.77 25.033 9.07 12.094 3.44 4.595 1.78 2.386 1.10 1.477 0.69 0.928 0.48 0.649 0.27 0.3610 0.17 0.23


Ginkgoopsida and Pinopsida. This is probably just aresult of noise in the analysis having an inordinateeffect on this factor, which has the lowest eigenvalue(a similar effect was found in the higher ranked fac-tors in Sepkoski’s 1981 analysis).Factor 4 (Silurian – Devonian). This is dominated byZosterophyllopsida, with subsidiary Rhyniophytops-ida, Horneophytopsida, Trimerophytopsida andLycopsida (Table 2), and is partly equivalent to theDevonian Floras recognized by Niklas et al. (1983,1985). It also corresponds to the early phase of whatGray (1993) referred to as the Eutracheophytic Flora,but the latter also included plants such as the rhizo-morphic Lycopsida and early seed plants that arehere assigned to the Palaeophytic Flora (see alsoEdwards 1998; Le Hir et al. 2011). In the absence ofan existing name for anything that closely resemblesthe Factor 4 flora, we propose the new term ‘theEophytic Flora’.Factor 3 (Devonian – Permian). This is dominated byarborescent rhizomorphic Lycopsida, Pteropsidaferns, Equisetopsida and Cycadopsids (mainlyMedullosales), with some contribution from the Lyg-inopteridales and Progymnospermopsida (Table 2).This is essentially equivalent to the PalaeophyticFlora of Gothan (1912), except that the latter alsoincluded the early (Eophytic) floras. We propose toretain the term Palaeophytic Flora for the vegetationrepresented by factor 3 in our model.Factor 1 (Permian – Early Cretaceous). This is domi-nated by Pinopsida conifers, Ginkgoopsida and Pter-opsida ferns, with some significant contribution

from Bennettitopsida (Table 2), and is essentiallyequivalent to the Mesophytic Flora of Gothan(1912).Factor 2 (Middle Cretaceous – Neogene). This is over-whelmingly dominated by angiosperms (Table 2),with some contributions from Pteropsida ferns, andis equivalent to the Cenophytic Flora of Gothan(1912).

Using a similar approach to Sepkoski (1981), wetranslated the factor loadings for the stratigraphicalages into family diversities for each of the five florasthrough time (by squaring the loading for each fac-tor and multiplying it by the total family diversityfor each age). The results are shown in Figure 5.

Discussion

General trends in family diversities

Family diversity dynamics within classes show con-siderable variation (Fig. 2) and match the level ofvariation observed by Sepkoski (1981) for marineinvertebrates. Raup et al. (1973) were able to gener-ate a similar range of dynamic patterns from a sto-chastically simulated set of lineages. As pointed outby Raup (1977), however, this does not mean evolu-tionary processes have been random, but rather theywere subject to such a complex set of interactinginfluences that the resulting diversity patterns are inpractice unpredictable except in a probabilistic

Carbon-iferous

DevonianSilurian Permian Triassic Jurassic Cretaceous Palaeogene Neogene

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Fig. 4. Loadings of successive stratigraphical ages on the rotated factors from the five-factor model generated for family within classdiversity changes. Relative lengths of chronostratigraphical periods based on Cohen et al. (2013).


sense. Within the plant data, the most obviousfeature is that very few classes have become extinct;many of those that appear to have disappeared inFigure 2 are in fact pseudo-extinctions, where oneclass merely gave rise to a second class, such as theZosterophyllopsida–Lycopsida (Gensel 1992; Ken-rick & Crane 1997b) and Progymnospermopsida–Lyginopteridopsida (Rothwell & Serbet 1994). Thisis in marked contrast to the marine invertebrates,where there were numerous class-level extinctionsthrough geological time (Sepkoski 1981, fig. 1). Afew plant classes show a constriction in their diver-sity profiles near the Permian/Triassic boundary,notably the Pteropsida and Pinopsida, similar to thatrecorded in the record of marine faunas (Raup1979), but nothing is evident at the other major‘mass extinctions’ recorded by Raup & Sepkoski(1982) in the marine invertebrates in the late Devo-nian, and at the end of the Triassic and Cretaceousperiods.

There are notable similarities between the totalfamily diversity curve for vascular plants shown inFigure 5 and the curve produced for terrestrial tetra-pod families by Benton (1987; see also Sepkoski1990): a rise and then decline in overall diversityduring Palaeozoic times, a gradual recovery and thenequilibrium during most of Mesozoic times, andthen a very rapid diversification from Late Mesozoictimes onwards (Fig. 6). The only real difference isthat the Palaeozoic diversity peak in the tetrapodslasted a little longer than the equivalent for plants(possibly a taphonomic effect, as the red-beds thatdominate the Permian sequences of Euramerica tendto favour preservation of bones over plant remains –see Anderson et al. 1998) and the dip in tetrapod

diversity occurring rather later than that of plants, inEarly Jurassic times. Sepkoski’s (1981, 1984) familydiversity curve for marine invertebrates is in contrastquite different, with a clear plateau being reachedduring Late Palaeozoic times, a sudden and sharpreduction at the Permian/Triassic boundary, andthen a progressive sub-linear rise in diversitythrough post-Palaeozoic times with just a minortemporary downturn at the Cretaceous-Palaeogeneboundary (Fig. 7). We should perhaps not find thesesimilarities and differences surprising given that weare looking at diversities in very similar terrestrialhabitats for the vascular plants and tetrapods, incontrast to the marine habitats of the invertebrates,although what the relative constraints were in thesetwo habitats remains uncertain. Benton (2001)argued that there may not have been the same den-sity constraints on taxonomic diversification on landas has been suggested for the marine realm (by Sep-koski 1990), although Stanley (2007) has subse-quently suggested that those ecological constraintson taxonomic diversification in marine faunas mayhave been exaggerated.

The species diversity curve produced for vascularplants by Niklas et al. (1983) agrees with our familydiversity curve in that there are no significant dips atthe Triassic/Jurassic and Cretaceous/Neogeneboundaries, as seen with the marine invertebrates.Otherwise, however, the Niklas et al. species curve israther different, following an essentially logistic pat-tern for the Palaeozoic Era, a slight dip at the Perm-ian/Triassic boundary, followed by an exponentialgrowth through Mesozoic and Cenozoic times.Experience with marine invertebrates suggests thattaxonomic rank should not have a dramatic effect

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Fig. 5. Changing family diversities within each of the five Evolutionary Floras indicated by the five-factor model described in this paper.The method of calculation is described in the text. The thick line shows the total family diversities through time, and the gap below itand the shaded area represents the small part of total diversity pattern not explained by the model. Relative lengths of chronostratigraphi-cal periods based on Cohen et al. (2013).


on long-term diversity curves (Sepkoski & Kendrick1993; Robeck et al. 2000; Smith 2007), and so it istempting to explain these discrepancies in terms ofthe distortions that are inherently introduced whentrying to use palaeobotanical fossil species for diver-sity analyses. On the other hand, Raymond & Metz(1995) demonstrated that the generic (and by impli-cation species) Silurian–Devonian diversity curvewas significantly biased by sampling effort, and sothis may have caused the apparent logistic patternreported by Niklas et al. (1983).

Sampling bias is also likely to have had an effecton the family diversity curves; some correlation hasbeen demonstrated between diversity and rock out-crop area for both the marine invertebrate record(Smith 2001, 2007; Smith & McGowan 2007) andpalaeobotanical record (Cascales-Mi~nana et al.2013). This might, for instance, partly explain thesimilarity between the curves for palaeobotany andtetrapods, and their difference from the marineinvertebrate curve, as the former two are derived

from terrestrial deposits, which will have differentfluxions in outcrop area compared with marinedeposits. It is, nevertheless, possible to extract resid-ual values for diversity after removing the effect ofsampling bias (Cascales-Mi~nana et al. 2013), and theauthors have found that this approach can producebiologically meaningful results (work in progress).However, the effect of sampling bias on the presentstudy will be less significant as we are looking at thechanging proportions of the major plant groupsthrough time – those proportions are likely to be rel-atively unaffected by whether we have large or smallareas of outcrop (and therefore presumably more orless fossiliferous localities, although see Dunhill2012 and Dunhill et al. 2012 for a critique of thisassumption).

Evolutionary Floras and Faunas compared

The Rhyniophytic Flora has no obvious compari-son in the Sepkoski (1981) model; it may perhaps

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Groups

Fig. 6. Changes in standing diversity of families of terrestrial terapods as recorded by Benton (1985, 1987). ‘Modern Groups’ refer tofrogs, salamanders, lizards, snakes, turtles, crocodiles, birds and mammals. Redrawn from Benton (1987, fig. 1) with time-scale adjustedto correspond with the latest IUGS chronostratigraphical scheme (Cohen et al. 2013).

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Fig. 7. Part of the Sepkoski (1981, 1984) model of evolutionary faunas derived from family distributions of marine invertebrates. Theupper black line represents total diversity, including families not explained by the four factors. Redrawn from the post-mid-Silurian partof Sepkoski (1981, fig. 5), with time-scale adjusted to correspond with the latest IUGS chronostratigraphical scheme (Cohen et al. 2013).


be regarded as conceptually equivalent to thesoft-bodied Ediacaran Fauna, which was notincluded in Sepkoski’s data. However, there is somecomparison with the growth and decline of theCambrian Fauna and of the Eophytic Flora, andtheir replacement by the Palaeozoic Fauna and Pal-aeophytic Flora, respectively. This may be a conse-quence of them representing the biotas that firstmade a significant impact on their particular habi-tats. It is noteworthy that this part of the tracheo-phyte family diversity curve is very similar to thespecies and generic diversity curves produced by ear-lier authors (Knoll et al. 1984; Edwards & Davies1990; Raymond & Metz 1995); this is perhaps notsurprising as we are dealing here with small, herba-ceous plants, each of which is represented by a singlefossil species and fossil genus, in contrast to the lar-ger plants of later floras that are often recorded byseveral fossil taxa (Cleal & Thomas 2010).

Sepkoski’s (1981) Palaeozoic Fauna achieved aplateau in family numbers from Ordovician throughto the end of Permian times, when it was replaced bythe Modern Fauna following the Permian/Triassicmass extinction (Fig. 7). Sepkoski (1981, 1990)interpreted this logarithmic diversity curve as due tohabitat saturation in the marine realm, but accord-ing to Stanley (2007), it was more likely a conse-quence of major biotic crises. Either way, it is quitedifferent from the diversity pattern of the Palaeo-phytic Flora, which peaked in Middle Pennsylvaniantimes and then went into decline, being progressivelyreplaced by the Mesophytic Flora during Late Penn-sylvanian and Early Permian times.

The post-Palaeozoic diversity patterns are alsoquite different in the marine invertebrate faunas andterrestrial floras. In the former, there was a rapidrebound in family numbers through the TriassicPeriod as the Modern Fauna replaced the PalaeozoicFauna. Family diversity then continued to growexponentially, with just minor and temporaryreductions at the Triassic/Jurassic and Cretaceous-Palaeogene boundaries (Stanley 2007). With theterrestrial vegetation, in contrast, two quite distinctfloras can be recognized. The Mesophytic Floraunderwent a marked decline in diversity at thePermian/Triassic boundary but then, like the faunas,recovered rapidly during the Triassic Period. How-ever, by Late Triassic times, family diversity peaked,suffered a very minor decline at the Triassic/Jurassicboundary and then remained relatively stablethrough to mid-Cretaceous times. The Mesophyticdiversity curve thus seems to approximate to thetype of logarithmic curve described by Sepkoski(1981) for his Palaeozoic Fauna. This cannot beexplained by biotic crises as Stanley (2007)

attempted to do for the Palaeozoic Fauna; this was atime of relatively equable conditions in terrestrialhabitats. Equally, however, it is difficult to see how ahabitat saturation explanation can be invoked,unless the Mesophytic Flora was restricted to a muchnarrower range of habitats than we generallyassume.

The Mesophytic Flora went into decline in LateCretaceous times and was progressively replaced bythe Cenophytic Flora; by mid-Palaeogene times, theMesophytic Floras had effectively disappeared. TheCretaceous-Palaeogene biotic crisis that clearly influ-enced marine invertebrate faunas had no impact onfamily diversity in terrestrial vegetation; all plantfamilies that have been identified in the Maastrich-tian Stage are still extant today. The CenophyticFlora diversified exponentially during Palaeogenetimes but then started to slow down during the Neo-gene Period producing a logarithmic diversity curve.This is quite different from the diversity curve ofmarine faunas, which continued to increase expo-nentially to the present-day (Stanley 2007).

What drove the dynamics of EvolutionaryFloras?

Dynamic changes in the Evolutionary Faunas havebeen interpreted as a consequence of biotic crises(Sepkoski 1978, 1979, 1983; Hoffman & Fenster1986) and differences in origination and extinctionrates between the faunas (Stanley 2007). However,the changes between the Evolutionary Floras are notcoincident with the type of biotic crises identified inthe faunal record. Neither is there any significantevidence of reduced origination and extinction ratesamong tracheophytes: Cascales-Mi~nana & Cleal(2012) noted only a very minor decline in familyextinction rates through time, and Niklas et al.(1983, 1985) suggested that overall there had been amarked increase in speciation rates accompanied bya reduction in species duration.

The changes between the Evolutionary Florasinstead appear to be mainly the result of major evo-lutionary innovations in plants. For instance, thechange from Rhyniophytic Flora to Eophytic Florawas driven by improvements in plant vasculaturemost notably seen with the appearance of the Zoste-rophyllopsida and Trimerophytopsida (Kenrick &Crane 1997a). A thicker and more robust vascularstrand meant that plants were no longer reliant on asterome (Edwards et al. 1986) or possibly stem tur-gor to remain upright and so could grow taller(Knoll 1986a; Edwards & Davies 1990). This wasaccompanied by the development of monopo-dial branching of stems, although plants remained


architecturally relatively simple (Gensel & Andrews1984; Edwards & Davies 1990; Kenrick & Crane1997b). There were also changes in reproductivestructures, with sporangia developing in clusterssometimes resembling lax strobili and in some caseswith more pronounced dehiscence structures tofacilitate spore release (Edwards & Davies 1990). Theoverall result was that the rhyniophyte ‘turf’ thatcharacterized the very earliest vascular land plantvegetation was replaced by what is termed here theEophytic Flora (Knoll 1986a; Edwards & Davies1990).

The change from Eophytic Flora to PalaeophyticFlora during Late Devonian times can be largelyinterpreted as a result of the development of hetero-spory notably in the Lycopsida and Progymno-spermopsida and then shortly afterwards theappearance of the gymnosperms and other plantgroups in which megasporangia bear single viablemegaspores (DiMichele et al. 1989; Bateman &DiMichele 1994; Linkies et al. 2010). Plants werealso able to become larger and architecturally morecomplex due to the development of more complexvascular structures including secondary growth, axil-lary branching and more substantial rooting systems(Galtier 1988; Mosbrugger 1990; Kenrick & Crane1997a; Dunn 2006; Galtier & Meyer-Berthaud 2006)and planated leaves that improved photosynthesis(Boyce & Knoll 2002; Boyce 2005). All these devel-opments combined to allow plants to occupy amuch wider range of habitats, in turn resulting in asignificant increase in taxonomic diversity.

Late Cretaceous times saw the rise of the angio-sperms, whose more efficient reproductive and dis-persal strategies that often included symbioticvectors involving insects and other animals (Laban-deira & Currano 2013) allowed them to both out-compete the gymnosperms and increase significantlytheir rate of speciation (Wing & Tiffney 1987; Craneet al. 2000). This was also accompanied by a diversi-fication among the pteropsid ferns especially amongepiphytes that were adapting to the architecturallymore complex angiosperm-dominated forests (Schu-ettpelz & Pryer 2009). This resulting fundamentalchange in vegetation is reflected in the transitionfrom the Mesophytic Flora to the Cenophytic Flora.

The change from Palaeophytic Flora to Meso-phytic Flora was more complex (Knoll 1986b) andwas only partly affected by the Permian/Triassicboundary extinction event. It seems to have been lar-gely a result of the decline of the wetland vegetationthat dominated much of the tropical land duringPennsylvanian times and where much of the Palaeo-phytic taxonomic diversity developed (Phillips 1981;Phillips et al. 1985; Gastaldo et al. 1996; Cleal &

Thomas 2005; Cleal et al. 2012), and its replacementby Mesophytic vegetation that first developed inmore xeric, extra-basinal habitats (DiMichele &Aronson 1992). It has been established from palyno-logical evidence that Mesophytic style vegetationexisted in extra-basinal habitats in Pennsylvaniantimes (Zhou 1994; Dimitrova et al. 2011; van Hoofet al. 2013) and even occasionally in drier, basinalhabitats (Lyons & Darrah 1989). When viewed in aEuramerican context, the transition from Palaeophy-tic to Mesophytic vegetation seems to be essentially astory of a change to increasingly dry habitats duringLate Pennsylvanian and Permian times (Frederiksen1972; Kerp 1996; DiMichele et al. 2001, 2004, 2006;DiMichele & Chaney 2005; Chaney & DiMichele2007), resulting in a complex process of biomemigration and replacement (DiMichele et al. 2008)that was compared by DiMichele & Aronson (1992)to the onshore – offshore hypothesis invoked by Jab-lonski et al. (1983) to explain dynamic changes inmarine faunas. This change in terrestrial habitats hasin turn been linked with climate change (Gastaldoet al. 1996), tectonically induced landscape change(Cleal & Thomas 1999, 2005) or a combination ofthe two (Cleal et al. 2010, 2011).

However, when viewed in a global context thesituation was more complex (Rees 2002). It is nowevident that, although the tropical wetland habitatshad disappeared from Euramerica by Permiantimes, they persisted in China through the PermianPeriod (Havlena 1970; Hilton & Cleal 2007; Wanget al. 2012), where for a time they covered an evenlarger area than they had in Euramerica (Cleal &Thomas 2005). The current data suggest that therewas a loss of higher level taxonomic diversity inthese Chinese wetlands, especially in Middle Perm-ian times (Stevens et al. 2011), but this may be anartefact of the much lower level of research that hasbeen carried out on these fossil floras; taxonomicdiversity in the fossil record will only provide a rea-sonable record of the original biotic diversity if thatfossil record has been the subject of a long andintensive history of investigation, which has notreally been the case in China, at least comparedwith Euramerica. Recent work has already extendedthe ranges of a number of higher taxa in these Chi-nese floras (Wang 1983; Seyfullah et al. 2009), andevidence has come to light of the presence of otherhigher, possibly new plant taxa (Hilton & Li 2003);evidently, the diversity of these Permian Palaeophy-tic Floras may well be greater than we currentlyunderstand. Recent analysis of the data from SouthChina has suggested that the palaeobotanical recordacross the Permian/Triassic boundary may be inter-preted as a gradual floral reorganization and


evolutionary replacement, rather than a massextinction (Xiong & Wang 2011).

Within the Mesophytic Floras, the situation wasalso more complex than it seems at first sight.Although there was only a relatively minor reductionin taxonomic diversity in Mesophytic Floras at thePermian/Triassic boundary, studies on family distri-butions suggest that a significant floral turnover didin fact occur here (Anderson et al. 2007; Cleal &Thomas 2009; fig. 11.8; Cascales-Mi~nana & Cleal2012; see also Looy et al. 2001; Rees 2002; Knollet al. 2007). This was most notable in low latitudes,which had the most diverse Permian floras butwhere there were the most extreme environmentalperturbations in Late Permian times (Sun et al.2012). Permian Mesophytic vegetation was replacedduring Triassic times by vegetation that retained anessentially similar aspect in terms of reproductivebiology and ecology, but which consisted of a mainlydifferent but apparently related suite of plant fami-lies. It is tempting to seek the origins of these succes-sor Mesozoic Mesophytic families (which includemany of the still-extant fern and gymnosperm fami-lies) in the higher latitude Palaeozoic vegetation,which seems to have been less impacted by thePermian/Triassic boundary event (Rees 2002;Goman’kov 2005; Knoll et al. 2007); it is notablethat the Triassic Period as the ‘Heyday of the Gym-nosperms’ (Anderson & Anderson 2003) is mostevident in the southern mid-latitude fossil floras ofGondwana. Alternatively, Kerp et al. (2006) haveargued that at least some of the characteristic com-ponents of higher latitude Triassic vegetation hadtheir origins in low-latitude Permian vegetation andthat they dispersed pole-wards as a consequence ofthe end-Permian ecological perturbation (see alsoWang 1996; Spalletti et al. 2003). Whatever the ori-gins of the Mesozoic Mesophytic families ultimatelyprove to be, however, the results can be seen in theclear constriction of the family diversity profiles incertain classes through the Permian/Triassic bound-ary interval (Fig. 2).

Conclusions

The results of this analysis, with an apparent sim-plicity, show how the broad dynamics of vegetationhistory can be interpreted in terms of a series ofturnovers of large-scale floras. The resulting modelis not dramatically different from that suggested byearlier authors (Gothan 1912; Potoni�e 1921; Niklaset al. 1983) but has the merit of being based on anobjective mathematical analysis of empirical data

rather than a subjective interpretation of taxonomicranges. Interestingly, the main dynamic changesbetween these floras did not occur as abruptdisruptions; an incumbent flora underwent a grad-ual decline as it was progressively replaced by its suc-cessor. Thus, for example, we observe that the maindecline in the Palaeophytic Flora started in Late Car-boniferous times and progressed through Permiantimes, with the end-Permian crisis only confirmingthe progressive reduction of total taxonomic (fam-ily) diversity. This fact marks a strong differencebetween these floras and the Evolutionary Faunas ofSepkoski (1979, 1981, 1984, 1990), where thechanges between faunas seem to have been rathermore abrupt.

Sepkoski (1979, 1981, 1984, 1990) tried to explainthe dynamics of his Evolutionary Faunas in terms ofdifferences in their intrinsic rates of taxonomic orig-ination and extinction, but there is little that we cansee in the floras that would support a similar idea.Some authors (Hoffman & Fenster 1986; Stanley2007) have argued that the mass-extinction eventsidentified by Raup & Sepkoski (1982) in part con-trolled the dynamics of the Evolutionary Faunas, butagain there is no evidence that such events had a sig-nificant impact on the floras; the transitions betweenthe floras do not coincide with such events. Neitherdo the floras have any chronostratigraphic signifi-cance as originally implied by Gothan (1912);despite suggestions to the contrary (Kerp 1996,2000; DiMichele et al. 2008), it has been a long timesince most palaeobotanists have seen them in thatlight. The transitions between the floras tended to bethe result of complex, diachronous patterns ofbiome replacement, which in turn were the result oflarge-scale environmental changes (e.g. climate, sub-strate conditions) favouring plant groups with newlyappeared evolutionary innovations notably in repro-ductive biology (heterospory, ovules and flowers),architectural complexity and secondary growth. Ithas been argued (Kerp 1996, 2000; DiMichele et al.2008) that this very complexity in transition betweenthe floras is a reason for abandoning them as con-cepts, but in our view, this is missing the point – ofperhaps ‘not seeing the wood for the trees’. Thesefloras should not be seen as a means of describingdetailed patterns of vegetation change. Rather, theyreflect the overarching trajectory of vegetation his-tory, in particular of the major evolutionary changesin plants that impacted on their ability to widen therange of habitats that could be vegetated and thedegree to which those habitats could be ecologicallysegmented. In this sense, therefore, it would seemlegitimate to refer to them as Evolutionary Floras.


Acknowledgements. – B.C.-M. acknowledges the financial sup-port provided by Project ANR-2010-BLAN-607-02 ‘TERRES’.The paper was presented at the 2013 palaeobotany meeting ofthe Linnean Society, London, and we are grateful to colleaguesfor comments and suggestions made after the presentation.Thanks also go to Dr Arden Bashforth (Smithsonian Institution,Washington DC) and to another anonymous referee for theirconstructive comments.

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composition and dynamics of the great phanerozoic evolutionary floras

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